Time-Frequency Signal Synthesis and Its Application in Multimedia Watermark Detection

A novel approach is proposed in this thesis to synthesize the time domain chirp signal from the joint time-frequency distribution (TFD). The objective is to reconstruct the original signal from its corrupted version. The new signal synthesis technique is based on the Discrete Polynomial Phase Transform (DPPT) and the TFD of the signal to be synthesized. The TFD is used to separate the mono-component signals from a multi-component signal. The DPPT is then applied on the estimated mono-components to have a final synthesized version of the individual time domain signals. The candidate TFD to be used in the synthesis technique is chosen from a group of common TFDs based on their performance with different types of signals. The criteria for the comparison are joint time-frequency localization, low susceptibility to noise, cross-term suppression and the precision of the instantaneous frequency estimated from these distributions. Smoothed Psuedo Wigner-Ville Distribution is chosen as the processing TDFD in the proposed signal synthesis technique. The proposed chirp synthesis technique is applied to detect the presence of the chirp signal embedded as a watermark message in multimedia security applications. The technique can detect the presence of chirp signals from a corrupted chirp with a bit error rate up to signal synthesis is proved to be less than that of the detection method based on the Hough Radon Transform and the proposed signal synthesis technique may also be used as an error correction tool in other applications.

Time-Frequency Signal Synthesis and Its Application in Multimedia Watermark Detection

A novel approach is proposed in this thesis to synthesize the time domain chirp signal from the joint time-frequency distribution (TFD). The objective is to reconstruct the original signal from its corrupted version. The new signal synthesis technique is based on the Discrete Polynomial Phase Transform (DPPT) and the TFD of the signal to be synthesized. The TFD is used to separate the mono-component signals from a multi-component signal. The DPPT is then applied on the estimated mono-components to have a final synthesized version of the individual time domain signals. The candidate TFD to be used in the synthesis technique is chosen from a group of common TFDs based on their performance with different types of signals. The criteria for the comparison are joint time-frequency localization, low susceptibility to noise, cross-term suppression and the precision of the instantaneous frequency estimated from these distributions. Smoothed Psuedo Wigner-Ville Distribution is chosen as the processing TDFD in the proposed signal synthesis technique. The proposed chirp synthesis technique is applied to detect the presence of the chirp signal embedded as a watermark message in multimedia security applications. The technique can detect the presence of chirp signals from a corrupted chirp with a bit error rate up to signal synthesis is proved to be less than that of the detection method based on the Hough Radon Transform and the proposed signal synthesis technique may also be used as an error correction tool in other applications.

Vibration Parameters Study of Ship Structures Using Wavelet Analysis of Vibrogram

The study of the vibration parameters of ship structures is important for developing measures to ensure their reliable operation on ships. The commonly used analysis of vibrograms using the Continuous Fourier Transform (CFT) to accurately represent non-stationary functions in general and noise source signals in particular is unsuitable due to a number of drawbacks. The problems of spectral analysis and time-limited signal synthesis can be partially solved by switching to the Window Fourier Transform (WFT). The disadvantage of the WFT is that its calculation uses a fixed window, which cannot be adapted to the local properties of the signal. In order to get rid of this shortcoming for the analysis of vibrogram you can use wavelet transform. It also solves a number of other problems related to the processing of a noise signal. The word “wavelet” means small waves following each other (some sources have introduced the concept of “splash”). In a narrow sense, wavelets are a family of functions obtained by scaling and shifting a single, parent function. In a broad sense, wavelets are functions with frequency localization, whose average value is zero. The article shows the signs of a wavelet. Examples of the most common wavelet functions are given. The use of wavelet functions is proposed not only on the basis of time, but also frequency transformations. The implementation of the algorithm for analyzing vibration measurement data is proposed. An example of vibration measurement data and the results of their processing based on frequency wavelet analysis are given

Vibration Parameters Study of Ship Structures Using Wavelet Analysis of Vibrogram

The study of the vibration parameters of ship structures is important for developing measures to ensure their reliable operation on ships. The commonly used analysis of vibrograms using the Continuous Fourier Transform (CFT) to accurately represent non-stationary functions in general and noise source signals in particular is unsuitable due to a number of drawbacks. The problems of spectral analysis and time-limited signal synthesis can be partially solved by switching to the Window Fourier Transform (WFT). The disadvantage of the WFT is that its calculation uses a fixed window, which cannot be adapted to the local properties of the signal. In order to get rid of this shortcoming for the analysis of vibrogram you can use wavelet transform. It also solves a number of other problems related to the processing of a noise signal. The word “wavelet” means small waves following each other (some sources have introduced the concept of “splash”). In a narrow sense, wavelets are a family of functions obtained by scaling and shifting a single, parent function. In a broad sense, wavelets are functions with frequency localization, whose average value is zero. The article shows the signs of a wavelet. Examples of the most common wavelet functions are given. The use of wavelet functions is proposed not only on the basis of time, but also frequency transformations. The implementation of the algorithm for analyzing vibration measurement data is proposed. An example of vibration measurement data and the results of their processing based on frequency wavelet analysis are given

Symbiotic bacteria mediate volatile chemical signal synthesis in a large solitary mammal species

Mammalian chemosignals—or scent marks—are characterized by astounding chemical diversity, reflecting both complex biochemical pathways that produce them and rich information exchange with conspecifics. The microbiome of scent glands was thought to play prominent role in the chemical signal synthesis, with diverse microbiota metabolizing glandular products to produce odorants that may be used as chemosignals. Here, we use gas chromatography–mass spectrometry and metagenomic shotgun sequencing to explore this phenomenon in the anogenital gland secretions (AGS) of the giant panda (Ailuropoda melanoleuca). We find that this gland contains a diverse community of fermentative bacteria with enzymes that support metabolic pathways (e.g., lipid degradation) for the productions of volatile odorants specialized for chemical communication. We found quantitative and qualitative differences in the microbiota between AGS and digestive tract, a finding which was mirrored by differences among chemical compounds that could be used for olfactory communication. Volatile chemical compounds were more diverse and abundant in AGS than fecal samples, and our evidence suggests that metabolic pathways have been specialized for the synthesis of chemosignals for communication. The panda’s microbiome is rich with genes coding for enzymes that participate in the fermentation pathways producing chemical compounds commonly deployed in mammalian chemosignals. These findings illuminate the poorly understood phenomena involved in the role of symbiotic bacteria in the production of chemosignals.